The Federal Communications Commission rejected four controversial petitions targeting major news broadcasters Thursday, dispensing with the cases just days before Donald Trump reclaims the White House and installs a Republican majority on the commission. source

With advanced technologies like AI transforming the business landscape, IT organizations are struggling to find the right talent to keep pace. The gap between emerging technological capabilities and workforce skills is widening, and traditional approaches — such as hiring specialized professionals or offering occasional training — are no longer sufficient as they often lack the scalability and adaptability needed for long-term success. According to IDC’s July 2024 CIO Sentiment Survey, 26% of CIOs identify recruiting, retaining, and upskilling talent as their biggest challenge to success. Skill mismatches (31%) and inadequate training and development opportunities (29%) underscore the demand for talent as well as the difficulty in finding candidates with the right skills. The problem isn’t just the shortage of qualified candidates; it’s the lack of alignment between the skills available in the workforce and the skills organizations need. Take cybersecurity, for example. A staggering 21% of organizations report a severe shortage of skilled cybersecurity professionals, with another 30% finding it difficult to find suitable candidates. Only 8% of organizations have a relatively easy time finding qualified cybersecurity experts. This shortage puts additional pressure on existing IT staff and leaves organizations vulnerable to cyberthreats. As the pace of technological advancement accelerates, it’s becoming increasingly clear that solutions must balance immediate needs with long-term workforce transformation. Spoiler alert: The solution we will explore in this two-part series is generative AI (GenAI). But before we get into that, let’s talk about what steps CIOs have taken to ensure their teams are equipped to navigate this rapidly changing environment. Current strategies to address the IT skills gap Rather than relying solely on hiring external experts, many IT organizations are investing in their existing workforce and exploring innovative tools to empower their non-technical staff. Organizations have adopted several strategies to acquire and develop talent, as illustrated in the bar chart below. IDC’s CIO Sentiment Survey, July 2024 Cross-training or hiring line-of-business (LOB) staff to do IT: A notable 41% of organizations are cross-training or hiring internal LOB staff to perform IT functions. Leveraging current employees who already understand the company’s operations and culture can build a more versatile and adaptable workforce. This approach can help foster collaboration between IT and other departments, but while LOB staff bring valuable business insights, this approach doesn’t necessarily build the long-term technical expertise needed for the IT team to complete complex tasks. Devolving duties to LOB staff: 40% of organizations are delegating duties to non-IT staff through tools like no-code or low-code platforms. These tools enable employees to develop applications and automate processes without extensive programming knowledge. Using this strategy, LOB staff can quickly create solutions tailored to the company’s specific needs. However, without proper governance and oversight, this can lead to inconsistencies, security vulnerabilities, and technical debt. Additionally, while these tools are excellent for simple applications, they might not be suitable for more complex systems that require specialized IT expertise. Training programs: To bridge the skills gap, 34% of organizations are utilizing external training and certifications, while 28% are implementing internal upskilling programs. By investing in their current workforce, companies can equip employees with in-demand skills and prepare them for evolving roles. However, this approach isn’t always feasible, as it requires significant time, money, and commitment from both the organization and the employees — and continuous updating to keep pace with rapid technological changes. This indicates a strong effort by CIOs to bridge skills gaps and offer some relief, with some organizations reallocating internal talent and others investing in formal training programs. However, while these fragmented strategies address immediate needs, they lack scalability and a forward-thinking approach. Is there a transformative solution that meets current operational demands while also fostering future skill development to effectively close the skills gap? GenAI: A transformative solution to the IT skills gap Enter GenAI, which offers the potential to revolutionize how organizations address the IT skills gap. GenAI can augment workers’ capabilities, automate complex tasks, and facilitate continuous learning. It can play a pivotal role in filling the skills gap through several key applications, such as: Cybersecurity assistance: GenAI can monitor networks 24 x 7, detect anomalies, and respond to threats in real time, helping to compensate for the shortage of skilled cybersecurity professionals. Knowledge management: GenAI helps organize and retrieve organizational knowledge, making it easier for IT professionals to access the information they need to solve problems and learn new skills. Virtual assistants and IT support: GenAI-powered virtual assistants can handle routine or repetitive IT tasks — like resetting passwords, troubleshooting common software issues, managing access permissions, and monitoring system performance — reducing the workload and allowing IT staff to focus on more complex and strategic tasks. Continuous learning and development: With GenAI-driven learning platforms, IT and business workers can have customized training modules tailored to individual learning styles and skill levels that continuously update based on the latest trends and technologies. And more: These are just a few examples; GenAI has many applications and can be tailored to meet specific organizational needs. Despite the pressing challenges posed by the IT skills gap, many organizations hesitate to embrace GenAI’s transformative capabilities: Just 30% of companies plan to augment IT and business workers with GenAI, according to the CIO Sentiment Survey. This leaves a significant 70% who aren’t exploring this avenue. CIOs who act decisively now will gain a competitive edge by building adaptable, AI-ready teams. The next step is understanding how to implement GenAI effectively, from overcoming adoption barriers to change management — a topic we will explore in Part 2 of this series. Conclusion As organizations strive to keep pace with rapid technological advancements, the limitations of current strategies to address the IT skills gap become increasingly apparent. While current strategies address parts of the problem, they lack the scalability and foresight needed for long-term success. GenAI offers a unified solution that fills immediate gaps and sets the stage for a more resilient and innovative IT workforce. In Part 2, we’ll explore practical steps for CIOs to adopt GenAI,

Gemini features are now part of both Workspace Enterprise and Workspace Business without additional fees. On February 2024, I wrote a blog post declaring “You’re not switching to Google Workspace to use Gemini — yet.” Google aims to change that. Today, the company announced that it will include “the best of Google AI in Workspace Business and Enterprise plans” without the need to purchase an add-on. (Previously, Gemini for Workspace plans cost $20/user/month.) Google will now go to market with Workspace as a fully genAI-enabled productivity and collaboration suite, in contrast to Microsoft’s $30/user/month Microsoft 365 Copilot add-on. Google will raise its Workspace price, nominally, from $12/user/month to $14/user/month. Workforce Generative AI Can Be A Feature, Not A Product Driving higher productivity with generative AI has been no easy task. Approaches that embed genAI directly into the flow of work, like Microsoft 365 Copilot and Google Workspace, see higher usage than solutions that require employees to switch between applications. (Who wants to compose an email in a separate browser window, then cut and paste?) But until Google’s announcement, embedded solutions required expensive add-on licenses. Google’s bold move here: Reminds us that products can evolve into features. Forrester has long tracked the phenomenon of products becoming features; in 2014, we wrote about how Amazon Prime turned the music business into a feature of its Prime platform subscription. In 2020, we wrote about how the enterprise AI market isn’t as big as you think it is, because a lot of AI was already being expressed as a feature of existing software. Google is betting that the same will happen with genAI productivity and collaboration. Shows a case of a viable offering seeking monetization in other ways. Other companies in this space follow a similar approach. Zoom, for example, added genAI features to its core platform without an add-on subscription. The approach assumes that value can be captured via higher market share (acquiring customers) and retention (lower churn) effects. Google, with its small footprint, should be focused on the former. Tempts us to say that Google failed, but it could be a competitive boon. Some headlines will likely call this “commodification” or say that Google simply gave up because it couldn’t sell Gemini for Workspace. While there’s an element of truth to both, Google’s sales channel and customers may well celebrate. The move instantly refocuses Google’s value proposition and pricing, though, as we’ll see, it still won’t be for everyone. Google Workspace Belongs In Some Purchasing Discussions Yesterday, we released a new report, How To Build A Pragmatic Microsoft 365 Copilot Program, in which we argue that making Copilot valuable faces numerous obstacles, from measuring ROI to technical and performance challenges to a high employee training burden that isn’t being met. So M365 Copilot has vulnerabilities. But Workspace does, too; the training burden applies equally to employees using Gemini features, for example. It’s likely still not time for you to switch from Microsoft 365 to Google Workspace. But we also believe that: Google Workspace will become more competitive with Microsoft 365. Attractive pricing matters, especially when, at its new price, Google brings credible performance, a small but nontrivial roster of enterprise clients, and also some differentiated genAI features (including the innovative NotebookLM and Vids, a video-creation genAI tool). Microsoft 365 is embedded and has enduring strengths. Despite Google’s appeal, Microsoft 365’s ubiquity and quality remain hard to dislodge. Migrating M365 documents, SharePoint sites, and macros to Workspace remains a monumental effort. Plus, Microsoft 365 and M365 Copilot have genuine advocates among buyers. In addition to Copilot Studio, a range of Microsoft Azure services and development tools allows enterprises to create a wide range of applications. Increasingly, those applications can be accessed from inside Copilot. Microsoft will, however, feel pricing pressure. Building a business case for M365 Copilot that convinces the CFO to expand licenses broadly remains challenging. At most organizations, cohorts of users abandon Copilot, leading to employee license transfers, higher than expected training burdens, and less than productive outcomes. How long can Microsoft hold the line — and for how long — on $30/user/month? We’re betting the pricing strategy evolves. Next Steps For You? Let’s Talk You should consider Workspace if you are: 1) a startup (companies starting from scratch with little Microsoft legacy are more likely to adopt); 2) an SMB (small and medium businesses need fewer features and are more price-sensitive); 3) willing to segment your workforce (specific departments might benefit, even if the rest of the company uses Microsoft 365); and/or 4) in need of specific Google innovations, like Vids or NotebookLM. But regardless of whether you are already knee-deep in M365 Copilot, considering Workspace, or still haven’t jumped into any of these tools, your next steps will depend on your resources, needs, and AI readiness. Reach out to schedule a guidance session with me, and let’s get you where you need to go. source

By Adam Lidgett ( January 16, 2025, 8:45 PM EST) — One of the commissioners of the U.S. International Trade Commission, who had served as the agency’s leader for a year and a half, has decided to leave and make the move to WilmerHale, according to the ITC…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Customer relationship management (CRM) systems assist companies with customer interactions while also managing customer data, and streamlining business processes. When properly utilized, a CRM tool allows sales teams to interact with and convert prospective leads into paying customers while maintaining strong relationships with existing clientele. Routine daily tasks like data entry, lead assignments, and email follow-ups are essential for customer conversion and retention, but they are often viewed as being redundant and time-consuming for sales reps. CRM automation can reduce the workload of sales professionals and free up their time to be used in other important areas like lead generation, lead nurturing, and personalized phone calls to clients. 1 monday CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 2 Pipedrive CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 3 Creatio CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Medium, Large, Enterprise Features Dashboard, Document Management / Sharing, Email / Marketing Automation, and more What is CRM automation? CRM automation leverages technology to streamline and automate repetitive tasks and processes within CRM systems. Eliminating the need for manual handling of customer data entry, lead tracking, and follow-ups allows businesses to design workflows that execute these tasks automatically. Common automated functions include: Sending lead-nurturing emails. Scheduling follow-ups. Reminding teams of critical deadlines. Routing leads to appropriate sales representatives. These automations are based on predefined rules and conditions in order to maintain consistency in customer interactions, reduce human error, and enable employees to focus more on strategic, high-value activities. Additionally, CRM automation enhances customer experiences by enabling personalized interactions at scale. Automated customer segmentation can be based on behavior or demographics, so that businesses can tailor their communications to the unique needs of each group. Advanced CRM systems, powered by data analytics and AI-driven insights, can predict customer needs, identify potential issues, and recommend the next best actions for sales and support teams. This level of personalization and insight-driven engagement strengthens customer relationships, increases satisfaction, and ultimately drives revenue growth. What are some benefits of automating CRM? CRM automation comes with a host of benefits that can add significant value to your business. For example, automation can seamlessly capture engagement activities, like email and event details, and store them in a centralized hub for easy access by team leaders and team members alike. AI features can also significantly enhance sales processes by identifying high-potential leads and recommending follow-up actions based on previously successful interactions with similar customers. It can even flag at-risk leads and suggest optimal strategies to close deals more efficiently. Automation further supports accurate product and pricing data, which promotes more informed decision-making. This allows teams to respond swiftly to market changes with updated products, bundles, and promotions, improving overall responsiveness. Best CRM Software How to implement CRM automation Start by identifying repetitive tasks, like data entry, follow-ups, and lead assignments. Find areas where automation can help improve efficiency. This would include tasks such as sending welcome emails or updating records after calls. Choose a CRM with strong automation features. Set goals for what you want your automation to achieve. Design workflows with defined triggers and actions in mind. Thoroughly test each workflow and make adjustments based on team feedback. Connect your CRM with other existing tools for seamless data updates. Train your team on these new processes and continue to gather feedback. Regularly track performance to refine workflows and adapt to emerging business needs. CRM automation best practices Best practices for CRM automation start with setting clear goals and targeting high-impact, repetitive tasks. Design workflows that prioritize customer experiences, adding value at each step and maintaining personalized interactions. Use segmentation and data-driven insights to deliver tailored content and targeted offers to boost engagement and enhance customer satisfaction. Continuously test and optimize workflows based on performance metrics and team insights as well. And integrate your CRM with other essential tools for consistent, accurate data across platforms. Finally, keep your team trained on automated processes to use automation more efficiently and recognize when manual input is needed to improve the overall customer experience. CRM automation tools Top CRM automation tools include HubSpot, Salesforce, and Zoho CRM. Other notable tools for specific use cases include Pipedrive, ActiveCampaign, and Freshsales. HubSpot HubSpot excels in email marketing and lead nurturing, which are ideal features for small and midsize businesses. Salesforce Salesforce offers advanced customization options supporting complex workflows for small and large enterprises. Zoho CRM Zoho CRM enables multi-channel automation across email, SMS, and social media for comprehensive customer engagement. Pipedrive Pipedrive focuses on sales automation, streamlining follow-ups, and pipeline management for teams with a large volume of leads. ActiveCampaign ActiveCampaign combines CRM with marketing automation, making it ideal for small businesses seeking integrated customer journey tools. Freshsales Freshsales offers lead scoring, workflows, and AI insights, which are perfect for automation-focused customer data management. FAQ What are the benefits of automated CRM? CRM automation streamlines repetitive tasks, improving efficiency and reducing errors. It enables personalized customer interactions at scale, enhances data accuracy, and boosts productivity. Automated insights allow for better decision-making, while seamless workflows improve customer satisfaction and drive sales growth. What is CRM workflow automation? CRM workflow automation uses rules and triggers to streamline repetitive tasks, such as lead follow-ups, data entry, and email responses. It ensures consistent, timely actions across customer journeys, improving team productivity, and enhancing customer experience by automating key steps in sales and support processes. Why do we need an automated CRM application? An automated CRM boosts efficiency by handling repetitive tasks, ensures timely, personalized interactions, and maintains accurate data. It frees up teams to focus on strategic work, enhances customer satisfaction, and drives revenue growth through consistent sales processes. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Europe’s Imec.xpand is spinning out memory chip firm Vertical Compute in a seed investment round worth $20.5 million. Founded by CEO Sylvain Dubois (ex-Google) and CTO Sebastien Couet (ex-imec), today announced that it successfully closed a seed investment $20.5 million, or 20 million euros. The round was led by Imec.xpand and supported by a strong investor base including Eurazeo, XAnge, Vector Gestion and imec. The funding will support Vertical Compute’s ambition to develop a novel vertical integrated memory and compute technology, unlocking a new generation of AI applications. Vertical Compute’s technology will have a transformative impact, enabling next-generation applications with unparalleled efficiency and privacy. By minimizing data movement and bringing large data closer to computation, the innovation ensures energy savings of up to 80%, unlocks hyper-personalized AI solutions, and eliminates the need for remote data transfers, protecting user privacy. “Memory technologies face limitations in both density and performance scaling, while processor performance continues to surge. The extreme data access requirements of AI workloads exacerbate this challenge, making it imperative to overcome the memory wall to enable the next wave of AI innovations. We believe going Vertical is the path to 100X gains”, said Sébastien Couet, CTO of Vertical Compute, in a statement. Tackling the Memory Wall The rapid advancements in large language models and generative AI are transforming virtually all industries at an unprecedented pace. However, these large-scale AI models still heavily rely on complex cloud infrastructure and high bandwidth memories, leading to data transfer latency, high energy consumption and sending sensitive data to distant servers. Edge computing can address these issues, but inferencing large AI models on smartphones, PCs or smart home devices faces significant cost, power and scalability constraints. The big underlying problem is the ‘memory wall’. Static Random Access Memory (SRAM), integrated as caches of the CPU or GPU, is fast but very small and expensive. Dynamic Random-Access Memory (DRAM), the main memory of computer systems, is larger but expensive and energy consuming. The scaling of both memory technologies in density and performance is slowing down while processor speeds and market needs keep increasing, causing a significant bottleneck. This problem is rapidly escalating due to the surging demand for AI workloads, requiring vast amounts of data to be accessed quickly. Overcoming this memory wall is crucial for advancing AI inference. Innovating with Vertical Compute’s Chiplet Technology Vertical Compute is spinning out of Imec. The convergence of large-scale AI models and edge computing calls for a transformative shift in the way data is processed. Vertical Compute will capture this opportunity by developing chiplet-based solutions — which take a modular approach to chip design — leveraging a new way to store bits in a high aspect ratio vertical structure. The concept behind Vertical Compute’s core patented technology has been invented by Sebastien Couet, Imec’s former Magnetic Program Director. The core innovation resides in the integration of vertical data lanes on top of computation units. It has the potential to outperform DRAM in terms of density, cost and energy, by reducing data movements from centimeters to nanometers. This promising technology, coupled with an ambitious commercialization plan, has led to the creation of this new semiconductor venture. “The surge in data-intensive applications like generative AI demands a drastic new approach to transferring data between computing cores and memory units. Our solution is designed to overcome the fundamental scaling limitations of memory technologies by going vertical. We are committed to unlocking the full potential of large language models on the edge without any compromise,” said Sylvain Dubois, CEO of Vertical Compute, in a statement. “We want to recruit the very best from all over Europe and finally put Europe at the forefront in terms of tech”, said Dubois. Driving Recruitment and Growth Vertical Compute is headquartered in Louvain-La-Neuve (BE), with its main R&D offices in Leuven (BE), Grenoble (FR) and Nice (FR). The company is recruiting an elite team of engineers to support its ambitious R&D goals and accelerate the development and commercialization of its chiplet-based technology. This seed investment round highlights the confidence in the leadership team’s capabilities and the disruptive potential of this game-changing technology. We could not be more excited to collaborate with Sylvain, Sebastien and their team and to help them to achieve their ambitious goals”, said Tom Vanhoutte from Imec.xpand, in a statement. “We are confident that, with the ongoing support of our teams and ecosystem, Vertical Compute can become a disruptor in the semiconductor industry. The strong international investor base shows that we are not alone in this belief,” said Patrick Vandenameele, co-COO at Imec, in a statement. Vertical Compute was founded in 2024 to solve the memory bottleneck in computer systems. source

It’s a particularly relevant question now, as governments consider more AI regulations, the courts deal with AI-related cases, and society grapples with the real-world sometimes tragic consequences of the technology. Sack says companies need to consider what ethical, legal, and compliance implications could arise from their AI strategies and use cases and address those earlier rather than later. “Ethical, legal, and compliance preparedness helps companies anticipate potential legal issues and ethical dilemmas, safeguarding the company against risks and reputational damage,” he says. “If ethical, legal, and compliance issues are unaddressed, CIOs should develop comprehensive policies and guidelines. Additionally, they should consult with legal experts to navigate regulations and establish oversight committees.” 9. What’s our risk tolerance, and what safeguards are necessary to ensure safe, secure, ethical use of AI? Manry says such questions are top of mind at her company. “At Vanguard, we are focused on ethical and responsible AI adoption through experimentation, training, and ideation,” she says. “Resulting from senior leader and crew [employee] perspectives, our primary generative AI experimentation thus far has focused on code creation, content creation, and searching and summarizing information.” She advises others to take a similar approach. “CIOs must assess risk tolerance and implement safeguards for generative AI to address safety, security, and ethical concerns. By establishing healthy safeguards like data protection protocols and ethical guardrails, CIOs ensure responsible AI use and minimize risks,” she says. “Establish an AI governance framework that defines the organizations risk tolerance, and patterns of acceptable use based on data sensitivity, allowing low risk generative AI use cases to be fast-tracked while applying more rigorous evaluation on higher-risk applications. “This approach enables teams to innovate safely and efficiently, while ensuring more rigorous safeguards for use cases involving sensitive data. By implementing robust security measures, bias mitigation techniques, and an ethical review process, CIOs can minimize risks and ensure responsible use of AI.” Not all organizations are there yet, though: Data governance research from Lumenalta, which delivers custom digital solutions, found that only 33% of organizations have implemented proactive risk management strategies for AI governance. 10. Am I engaging with the business to answer questions? CIOs shouldn’t be going it alone, says Sesh Iyer, managing director, senior partner and North America co-chair of BCG X, the tech build and design division of Boston Consulting Group. “CIOs must ask themselves whether they are engaging with the business to deliver value with generative AI, whether there is a clear focus on gen AI with a defined pathway to achieving a meaningful return on investments within 12 months, whether they are leveraging the power of the digital ecosystem to support their gen AI agendas, [and] whether they have a clear plan to extract and use data at scale to achieve these goals,” Iyer says. “These questions are crucial for CIOs to ensure they are delivering value, targeting spend effectively to achieve returns, and considering velocity-to-value — leveraging intellectual property and products from a broader ecosystem to reach value faster. Also, they must determine whether they have the ‘digital fuel’ (i.e., data and infrastructure) needed to achieve these AI-driven outcomes.” He advises CIOs to “sit down with the business to devise or refine an integrated ambition agenda” and “develop clear business cases that demonstrate returns within 12 months, establish a robust ecosystem strategy, and actively engage with partners to maximize value.” source

Creating, organizing, and sharing computation documents is essential in programming and data sciences. Most people turn to one of two popular tools — Google Colab and Jupyter Notebook — to help them manage their files. SEE: Learn how to become a data scientist. Image: Google Colab What is Google Colab? Google Colab is a tool offered by Google Research that allows users to write and execute Python code in their web browsers. Colab is based on Jupyter open source and allows you to create and share hosted computation files in the cloud without downloading or installing anything. Image: Jupyter What is Jupyter Notebook? Jupyter is the original free, open-source, web-based interactive computing platform spun from the IPython Project; Jupyter Notebook is a web application that allows users to create and share computation documents. 1 Quickbase Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Small, Medium, Large, Enterprise Features Agile Development, Analytics / Reports, API, and more Google Colab vs. Jupyter Notebook: Comparison table Software Google Colab Jupyter Notebook Starting price $9.99 per month Free Free plan Yes Yes Cloud based Yes No File syncing Yes No File sharing Yes No Library install No Yes File view without install Yes Yes Google Colab and Jupyter Notebook: Pricing Google Colab and Jupyter Notebook are both free to use. Jupyter Notebook was released as an open-source tool under the liberal terms of the modified BSD license, making it 100% free to use. Although Google Colab is also free, you may have to pay for advanced features as your computing needs increase. The following are the paid plans offered by Google Colab: Pay As You Go: For this plan, there are no fixed subscription fees; you only pay for what you use. Colab Pro: For $9.99 per month, you get 100 compute units, access to higher memory machines, and the ability to use a terminal with the connected virtual machine. Colab Pro+: For $49.99 monthly, you’ll get 500 compute units, faster GPUs, and background execution capability. Feature comparison: Google Colab vs. Jupyter Notebook Cloud-based Google Colab’s major differentiator from Jupyter Notebook is that it’s cloud-based, and Jupyter isn’t. If you work in Google Collab, you don’t have to worry about downloading and installing anything to your hardware. It also means that you can rest easily knowing that your work will autosave and back up to the cloud without you having to do anything. Google Colab homepage. Google Colab is great if you need to work across multiple devices — such as one computer at home and one at work or a laptop and a tablet — because it syncs seamlessly across devices. In contrast, Jupyter Notebook is run on your local machine, and files are saved to your hard disk. Jupyter offers an autosaving interval that you can change but doesn’t back up to a cloud. Therefore, if your machine is affected, you’re out of luck. Jupyter can’t sync or share your files across devices without a third-party file-sharing service like Dropbox or GitHub. Dashboard layout on Jupyter Notebook. Collaboration We couldn’t talk about Jupyter Notebook versus Google Colab without mentioning collaboration. As the name suggests, Google Colab is built to make it easy to share your notebooks with anyone — even if they’re not a data scientist. Other people can view your notebook without downloading any software — a big advantage if you regularly work with nontechies who need to access the files. Google Colab shareable dashboard for experiments. Conversely, anyone else must install Jupyter Notebook on their device to share their notebooks. This won’t be a hindrance if you solely work with developers, data scientists, and other tech people who will already have Jupyter installed. If you work on a more diverse team, then you might want to consider Google Colab because sharing files is easier. Library install Since Google Colab is cloud-based, the tool comes preinstalled with various libraries. This means that you don’t have to separate precious disk space or time to download the libraries manually. The free version also comes with a certain level of graphic processing units, memory, and run time, which can fluctuate. You can upgrade to one of the paid plans if additional capacity is needed. Google doesn’t disclose limits for any of its Colab plans due to the need for flexibility. With Jupyter Notebook, you’ll need to install each library you’d like to use onto your device using pip or another package manager. You’ll also be limited by your computer’s available RAM, disk space, GPU, and CPU. Having the notebooks stored on your hardware is more secure than in a third-party cloud. Therefore, the manual library installation can be a plus for sensitive data. R Scripts Both Google Colab and Jupyter Notebook allow users to run R scripts, though they are primarily designed for Python. In Google Colab, users can now select to work with R by selecting it within the Runtime menu. For Jupyter Notebook, users must install an R kernel to work with R on their computer. Google Colab pros and cons Pros Straightforward interface that’s easy to navigate. Access GPU and TPU runtimes for free. Import compatible machine learning and data science projects from other sources. Automatic version control similar to Google Docs. Real-time collaboration capability. Integrates with other tools, including GitHub, Jupyter Notebook, BLACKBOX AI, Codeium, CodeSquire, Google Workspace, Neptune.ai, StrongDM, Google Drive and more. Cons The free plan gives you limited resources. Some users reported issues with the speed of loading new databases and data frames that are present offline. Jupyter Notebook pros and cons Pros Modern, intuitive, and interactive user interface. Supports markdown language for documentation. Interactive interface makes it easy for users to share images, code, and text in one place. Supports multiple programming languages, including Python, R, and Julia. Cons Some users reported that the software gets slow or crashes sometimes when working with large datasets or carrying

With rich resources like a growing physical infrastructure and subsea cable network, Africa is uniquely positioned to emerge as a leader among today’s developing economies. A key factor in this potential is the improvement of  internet connection in Africa, which is central to facilitating the continent’s digital transformation. The African Union commits to growing Africa’s already burgeoning digital economy through The Digital Transformation Strategy for Africa (2020-2030), stating: “Innovations and digitalization are stimulating job creation and contributing to addressing poverty, reducing inequality, facilitating the delivery of goods and services, and contributing to the achievement of Agenda 2063 and the Sustainable Development Goals”1 Additionally, the continent is young with a median age of 20 years, and experiencing population growth with its 1.4 billion inhabitants making up 15% of the global population. This bodes well for growth in market size, GDP, and a population of digitally fluent consumers. Public and private sector efforts to boost Africa’s digital economy Global public and private institutions recognize Africa’s position as an emerging digital economy on the world stage. For instance, the U.S., European Union (EU), China, and India all have strategic programs in place for a solid digital infrastructure on the African continent. The foreign direct investment (FDI) sector financed $30 billion in sustainability projects, often referred to as “global greenfield megaprojects,” according to the UN’s latest World Investment Report. Barriers to Africa’s digital transformation In the near term, Africa’s land-based (terrestrial) infrastructure can hinder the strides forward many see on the horizon for the continent. For data center capacity to spread to more regions of Africa, there will need to be a major effort to create structure for overland routes. Additionally, Africa needs 500,000 kilometers of fiber-optic cable construction to connect the continent, says the International Finance Corporation (IFC). For enterprises to leap over these boundaries, they need partners with knowledge, sophistication, and a keen understanding of how business works from both a continental and a regional perspective, such as those offering specialized services like colocation in Africa. The future of greater digital access to the African economy In this article, we’ll provide an overview of Digital Realty’s capabilities to connect enterprises to the opportunities on the African continent, touching on topics such as: The growth of the digital economy in Africa Africa’s digital infrastructure both now and in the future Digital Realty’s unique positioning as a digital transformation leader in Africa Potential challenges and opportunities for leading enterprises expanding to the African continent First, we will highlight interesting developments and results from efforts to provide greater digital access to the African economy. The growth of the digital economy in Africa Since 2020, the African Union (AU) has partnered with public and private institutions to fund its goal of uniting the continent through universal internet access. This attracted billions of dollars for digital infrastructure investments in Africa. Here’s a summary of the results so far as researched by the World Bank: 115% – Between 2016 and 2021 internet users increased by 115% in Sub-Saharan Africa 160 million – The number of Africans who gained broadband access between 2019 and 2022 191 million – New recipients or senders of digital payments between 2014 and 2022 The African Union enacted a 10-year strategy to enhance Africa’s digital economy in February 2020. The release of the Digital Transformation Strategy for Africa attracted financial support from the World Bank which set off a series of funding initiatives spanning the globe and the public and private sectors. Government investment leads to growth of Africa’s digital economy AU efforts lead to World Bank investment. One year after the AU’s digital transformation strategy, the World Bank launched the All Africa Digital Economy Moonshot. This initiative aims to “digitally connect every individual, business, and government in Africa by 2030.” Results: By January 2024, World Bank closed on $731.8 million in financial commitments across 11 digital transformation projects across Sub-Saharan Africa. The organization also secured $2.8 billion for 24 more digital development projects since 2014. The EU launched the EU-Africa Global Gateway Investment Package of €150 billion in investments. In addition to sustainability, climate resilience, and biodiversity projects, the Global Gateway aims to fast-track universal access to reliable internet in Africa by 2030. Progress: The Global Gateway project features the AU-EU Digital4Development (D4D) Hub, connecting North Africa to EU countries with an extension into West Africa via Dakar, Senegal. (European Commission) The U.S. launched the Digital Transformation with Africa Initiative (DTA) in December 2022, committing $800 million to the continent’s digital transformation journey. (Carnegie Endowment for International Peace) Results: In its first year, the DTA funded $82 million in four all-Africa initiatives and more than 20 regional projects focused on country-specific goals. (Carnegie Africa analysis) Of particular interest is the investment in: Digital trade alliances Funding infrastructure of information and communications technology (ICT) Feasibility studies to expand Internet access to rural parts of Africa These efforts have also led to a cascade of private investments from some of the world’s largest technology enterprises. Future impact of public and private digital infrastructure investment in Africa One purpose of these investments is to leverage Africa’s unique status as the fastest growing continent by population and gross domestic product (GDP), according to United Nations (UN) and African Development Bank figures. The ultimate payoff will be Africa’s contribution of $180 billion in GDP to the global economy by 2025 and a potential $712 billion by 2050. Leading enterprises know the time is now to partner with experts with an established presence in Africa’s digital infrastructure transformation. Digital infrastructure critical to Africa’s data sovereignty Currently, Africa represents two percent of the world’s data center footprint which greatly affects the continent’s data sovereignty efforts.2 The data regulations landscape on the continent remains fluid, but it’s also a top priority within established data economies in Africa. For example, in 2023 the Data Protection Act became law in Nigeria, which provides data protection guardrails that previously did not exist. Africa’s data center landscapeThis push for data sovereignty and more stringent data regulation calls for enterprises to establish partnerships with an experienced multi-tenant data center (MTDC) operator with a wide